It’s been an exceptional CES for NEXYAD :
. a major firm of car exlectronics presented on their booth 2 products that integrate our SafetyNex API
. we has about 30 qualified meeting (and we took good shoes J)

Between two meetings, NEXYAD has visited the gigantic section for Automotive in CES 2019 : Central Plaza and North Hall + a part of Central Hall
Four major trends caught our interest : Lidar, Vocal Driver Assistant, Autonomous Pods and French Tech.

LIDAR

The lidar (light detection and ranging) becomes an inescapable technology that will be present inside tomorrow vehicles, whether for the ADAS or for the autonomous vehicle. Investors seem to have made big bets on and yesterday Lidar actors still non-existent or tiny have now clearly visible in the aisles of the show. Lidar can be electromechanical or solid-state much cheaper technology. It is easy to split the following lidar companies in two: the north americans and others.

In California, we have Ouster that sided with the high resolution; and Cepton that provides long range lidars; also Velodyne with a whole range of different products for different uses; Then AEye with its iDar combination of camera and lidar. In Montana, there is Blackmore providing solid state technology; In North Carolina, a new comer Sense Photonics. And the Canadian Leddartech solid state technology for mass deployment thru a chip for perception analysis. LeddarTech is member of the MOVEO ADAS Group with NEXYAD and a dozen of other high-tech companies for intelligent mobility.

RoboSense the Chinese company proposes several technologies: mechanical, solid state, laser scanner and also perception algorithms. Innoviz Technologies the israeli makes solid state and software perception. In South Korea there is SOS Lab with a product for self driving cars.

LeddarVU & LeddarTech Cocoon

VOCAL DRIVER ASSISTANT

Everybody heard about vocal assistant, it is very popular for home use. Of course, those assistants arrive now into cars. Vocal Driver assistants make spoken human interaction with computers possible, using speech recognition to understand spoken commands and questions in natural language, and typically text to speech to play a reply. They are the primary way of interacting with virtual assistants on smartphones and smart speakers.

Difficult to miss Hey Google for example at CES this year. Besides Hey Google, there is OK Google and Google Allo. Google announces major automotive partnership with Renault-Nissan-Mitsubishi to integrate its Android System into their future cars. Let’s bet that their Vocal Driving Assistant will be in the deal.

Nuance is the pure player of this domain and showed this year an impressive new release of their Dragon Drive that brings the connected car to life through a natural language voice interface.

IBM Watson Assistant for Connected Vehicles is a digital assistant designed to enhance in-vehicle experiences, helping the automotive industry better understand and interact with drivers and passengers.

On the Pionner Booth, was demonstrated a Proactive Telematics product on smartphone with a beacon, and also a dashcam. Those 2 products send to driver vocal alerts before difficult ans dangerous situations and allow then to avoid accidents. Another way to assist driver (the Vocal Driving Assistant that can save your life).

AUTONOMOUS PODS & SHUTTLES

Most of the Autonomous Vehicle presented to CES were manufacturers or tier one companies intentions for future or stylish Demo Car. Besides, future seems to be moving away year by year, full autonomy will be difficult to reach most professional say.
The French Milla Group showed their electric Mobility POD and claims to be not only a prototype, but ready for different use cases: cities, industrial sites, University campuses, gated communities and resorts, at the commercial speed of 19Mph / 30Kmh with a price target compatible with massive deployment.

Note : Milla Group is member of the MOVEO ADAS Groupe through their subsidiary ISFM. One can notice that MOVEO ADAS Group had an incredible presence at this CES 2019.

Business France has brought together 26 high-tech companies, including NEXYAD, in the French Tech pavilion on Central Plaza, beside Here Technologies, Google, Faurecia, Valeo, etc… Half of those companies are members of ADAS Groupement, SME’s cluster inside larger competitiveness cluster MOVEO for Normandy and Paris area. ADAS Groupement offers numerous competences, services and products: EcoGyzer, eVA, I-Deep, LeddarCore, LeddarVu, Magic Vision CMOS, NeuroRBF, NSWeight, ObstaNex, Roadnex, RTMaps, SafetyNex, VisiNex, Widy Vision, Y-Konnect, 4DV-SIM, etc
– Sherpa Engineering‘s mission is to support its customers in the deployment of methodologies tooled by models to design and validate piloted systems.
– Intempora has developed RT-Maps for synchronizing and processing real-time data streams, and I-Deep a web-based application server for automating your algorithms test and validation procedures.
– Yogoko is an industry-leading communication solutions provider for the connected, cooperative & autonomous vehicles (CCAV) evolving in intelligent environments, their target markets are transport & mobility players: autonomous vehicle manufacturers, legacy automotive OEM and Tier1, for intelligent mobility solutions developer and integrators.
– Milla Group made the world premiere presentation of electric Mobility POD visible in the Pavillon. It was the big attraction of the pavilion. Mobility POD integrates Nexyad computer vision software modules RoadNex and soon ObstaNex and VisiNex and also SafetyNex on the top of the autonomous driving system to control Driving risk at each moment in real time.
– NEXYAD is the reference worldwide for risk driving computing, onboard, in real time, at each moment : what is the risk that driver (human or not) is currently taking. See LINK
– Geoflex allows to give a very appreciable accuracy to gnss (less than a meter) only with software, using a hundred antenna distributed on the globe.
– Benomad provides traditional GPS Navigation, EV Navigation, Intelligent Navigation for Collection Services, Mapping Services and Mapping SDK and Navigation API. NEXYAD API SafetyNex integrates the SDK of Benomad.

Luc Chatel president of PFA (Plateforme Française Automobile) , former french minister, and and Gerard Yahiaoui Nexyad CEO, discussing about the importance of real time driving risk computing for road safety improvement

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NEXYAD CEO speaker at XAVIER DALLOZ Conference at CES 2019

NEXYAD IS VERY PROUD FOR THEIR PARTICIPATION TO THE XAVIER DALLOZ CONFERENCE AT CES LAS VEGAS YESTERDAY

Hotel the Linq, wednesday january 10th.
It’s been a very interesting exchange about major trends on the CES this year, and NEXYAD presented an example of eXplanable Artificial Intelligence (XAI) to the automotive sector with their software component SafetyNex that computes at each moment in real time and with anticipation the risk that the driver is currently taking, with applications to :
. alerting human drivers and reduce accident rate by 20%
. making autonomous Driving systems much safer Thanks for this perfect organization.

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NEXYAD at Road Safety at Work Conference 2018

On December 17th, the 2nd edition of the National Symposium for Road Safety at Work was held at the French Ministry of Economy and Finance in Paris. This event was an opportunity to discuss the good practices implemented in this area for French companies and administrations. All day long, leaders, managers and experts gathered in front of 400 professionals, all types and sizes of corporates, to expose and cross theories, prevention strategies and feedback.

The 5th and 6th december, International Conference SIA CESA 5.0 took place in Versailles (just near the Château).
The goal of the organisers is to build a bridge between traditional automotive electronics and the new developments in vehicle electrification and digitalization as well as those from the world of consumer electronics and the Internet of Things.
The event has presented a great opportunity to understand how the automotive business will evolve over the next five years, with a focus on products and services that are likely to transition from other markets into use-cases for automotive.

Gérard Yahiaoui, Nexyad CEO was part of speakers for a new paper : Real Time Driving Risk Assessment for Onboard Accident Prevention : Application to Vocal Driving Risk Assistant, ADAS, and Autonomous Driving.

Here is a snapshot of car detection using RoadNex.
The big differenciation of ObstaNex is that is runs on a regular computer architecture (on a smartphone for instance) : no need for a heavy computing system. It is then much cheaper for mass volume deployment (new cars and aftermarket), because heavy computing architectures bring computing speed, but also high deployment cost, Energy consumption, heat, etc … not that good for onboard systems.

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FREE SPACE IN THE DIRECTION OF THE WHEEL ON SHORT DISTANCE (URBAN DRIVING APPLICATION)

FREE SPACE IN THE DIRECTION OF THE WHEEL ON SHORT DISTANCE (URBAN DRIVING APPLICATION) : ON A REGULAR COMPUTER ARCHITECTURE IN REAL TIME

RoadNex Short (free space detection in front of the car) runs on regular computer architectures (even on a smartphone). This module is made for fast sensor fusion with lidar and radar.
It works even on dusty roads, stones (image below), cobblestones, etc …
RoadNex brings interpretation (drivable surface), telemeter (radar; lidar, …) brings measurement precision (in mm).
No need for a big computer (it means deployment cost reduction).
This disrupts some electronics architectures big firms that try to convince car manufacturers to put their computers Inside cars, but they do not bring only computing efficiency (they do), they also bring additional cost, weight, heat, integration room need, etc …
RoadNex runs on a regular ARM chip (for instance) and may be the next generation solution.

The next generation autonomous POD (Shuttle) MILLA made by ISFM uses RoadNex and will be shown at CES Las Vegas in Jan 2019.
Come to see it.

Mobility is the cornerstone of contemporary societies and the changes underway will profoundly transform our uses and our movements.
Valued by our society, travel, in addition to being a social integration link, represents a freedom or a pleasure that can just as much be a servitude and source of exhaustion.
The LOTI Act of 1982 has led to focus on the centers of agglomeration, the stakes of today now focus on the peripheries low density and delivered to the car for 95% of trips.

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COMPARE YOUR AUTONOMOUS DRIVING SYSTEM TO BEST HUMAN DRIVERS IN TERMS OF DRIVING RISK TAKEN AT EVERY MOMENT

You want to measure the efficiency of your autonomous Driving system in terms of road safety ? Not easy with the regular validation methods : observing the number of km without accident is NOT the key. Indeed, accident is very rare for human driver anyway : on OCDE countries, 1 accident every 70 000 or 100 000 km (depending on the country), and on average 3 death every billion km !
We bring a way to build a metric between YOUR system and better human drivers … using our real time Driving risk assessment module SafetyNex.
A new solution for you to imagine validation process.

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FLEETS CAN TAKE BIG ADVANTAGE
OF REAL TIME DRIVING RISK ASSESSMENT

FLEETS CAN TAKE BIG ADVANTAGE OF REAL TIME DRIVING RISK ASSESSMENT : MORE PROFIT, LESS PERSONAL INJURIES, AWARDS FOR SAFER DRIVERS, etc.

SafetyNex is now under deployment by fleet managers :
. alerting drivers BEFORE danger can reduce accident rate by 20% : this is money for the fleet, and also less personal injuries and death
. risk profiles at the end of every trip can be used to deploy serious games : awards and coupons for safer drivers
. risk information sharing : if one driver took a big risk at a given area, then it is possible to automatically warn all the other drivers during a few minutes about a potential danger at this area : “stay vigilant”

Two kinds of fleet managers :
. Professional fleet management companies
. Internal fleet managers of big firms
. for the commercial fleet for instance
. for every employee through Corporate Social Responsability budget

Those ongoing deployments will make big money and will save lives at the same time.

Automotive industry is currently integrating into vehicles high level automations systems : automatic emergency braking, line keeping, etc … Those systems are complex : complex to do, complex to integrate together (as A system of systems), complex to validate.

NEXYAD STARTUP “COUP DE COEUR”
of THE MONDIAL PARIS MOTOR SHOW
with SafetyNex

Reporter expert in technology for FRANCE INFO, Gérard Feldzer made the summary of high-tech best inventions of this Mondial Paris Motor Show 2018 and talked about NEXYAD real time Driving risk assessment module that can alert driver when risk rises too much and then reduce accident rate by 20%.

Gérard Yahiaoui talk on front of more than 120 head représentatives of ORANGE Group, october 4th in Clamart.
Program :
. What is Artificial Intelligence ?
. Techniques developed by AI Researchers
. Different between AI and Complex Automation
. Business Models of AI in big companies
. Example of SafetyNex (Real Time Driving Risk Assessment)
. Autonomous Vehicle
. Vocal Driving Assessment
. Customers Acquisition
. Conclusion

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2018 WORLD AUTONOMOUS VEHICLE
ECOSYSTEM CONFERENCE at SHANGHAI

NEXYAD was kindly invited by ROSEDALE Products Engineering a Chinese Company to participate to this large event. We could discover the strongness of Chinese Automotive industry not well known in Europe, and appreciate kindness of officials of the organisation and chinese people in general. Many contacts were made for future business.

NEXYAD presented the story of professors, researchers and research engineers who decided to set up a company together (NEXYAD), and the result : 3 artificial perception software components, and a unique real time Driving risk software component, all Under integration by OEMs, Tier One Companies, Final Users, … NEXYAD will describe theoretical and practical aspects of those software componants in the next courses.

SafetyNex Real Time Driving Risk Assessment is used by car insurers to alert driver and to reduce accident rate by 20%, including personal injuries. The ROI of SafetyNex is then very easy to calculate and it is phenomenal !

CEO of NEXYAD (also Vice President of the French research cluster for mobility « MOV’EO ») was discussing today at a round table with Delphine GENY-STEPHANN, French State Secretary (Minister) of Industry. This took place at MOV’EO headquarters location in Saint-Etienne-du-Rouvray in Normandy, and it was about the future of French research clusters.
It’s been a very interesting information and points of view exchange session.
Thanks to Madame la Ministre.

NEXYAD is proud to announce that our Artificial Intelligence Algorithmes are used for Autonomous Driving Vehicles French High Tech Startup ISFM (Intelligent Systems for Mobility) selected Nexyad artificial intelligence algorithms for their Milla Smart Shuttle.

ISFM is one of the companies selected by the Ubimobility 2018 program

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SafetyNex episode 6 :
Five use cases when your eyes or sensors are not enough

SafetyNex can save your life part 1: Rainy Curve

SafetyNex can save your life part 2: Tight Curve

SafetyNex can save your life part 3: Priority

SafetyNex can save your life part 4: Stop Sign

SafetyNex can save your life part 5: Pedestrians Crossing

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Autonomous Driving Adaptative to situations with SafetyNex

HOW TO MAKE YOUR AUTONOMOUS DRIVING (AD) ADAPTIVE TO SITUATIONS THAT WERE NOT IMAGINED BEFORE

The true function of an autonomous vehicle is to move you from a point A to a point B, as quicly as possible, in comfort and safety (road safety : without accident and even without near-misses). Let’s talk about road safety because it is the job of NEXYAD with the Artificial Intelligence module SafetyNex.
20 times per second, SafetyNex estimates the risk that the driver (Driver is your Autonomous Driving system) takes. In an open world, new situations will happen (not in the scope of your scenarios) and if your AD is not adapted, risk will rise and SafetyNex will detect it. It opens the door to new strategies :
. Simple adaptive response : “if risk too high then slow down” for instance
. Complex adaptive system with deep Learning : if the response led to risk rising it is not the proper one … well it sounds you can improve your AD and even let it learn while it is in use in real vehicles !!!
And you even can modulate easily aggressiveness of your AD (necessary in dense urban areas).

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Broad Range Applications of
Real Time Driving Risk Assessment

Driving risk is not predictable from the so called “black spots” location, or from only driving behaviour. Driving risk appears when driving behaviour is not adapted to driving context, and particular, to road infrastructure complexity. There is no inherently bad driving behaviour (it depends on WHERE you drive: a disused airport ? in front of a school ? approaching an intersection ? risk is different for all those case). There is no inherently dangerous infrastructure and all automotive projects that record “black spots” are doomed to failure : they are places where few drivers in the past had a driving behaviour that was not appropriate to infrastructure complexity, and they died in accident. Thousands, millions, of other drivers did not have any accident at this location. What will this information bring to YOU ? Nothing ! It is necessary to evaluate adequation of YOUR driving behaviour to infrastructure complexity.
An AI module does that 20 times per second: SafetyNex.
Driving risk computed by SafetyNex is a core notion with lots of different applications : car insurance, fleet management, commerce, ADAS, Autonomous Driving, Vocal Driving Assistants, …

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Deep Learning for Onboard Applications: Hidden Trap

Now Deep Learning is used in onboard detection and pattern recognition applications. NEXYAD for instance uses Deep Learning in RoadNex (road detection without need of markings + detection of free space), and ObstaNex (obstacles detection).
But if you do not analyse your INDUSTRIAL project in detail, you may have bad surprises : everyone thinks he/she knows that the more numerous the training examples, the most accurate the KPIs. Let’s say you used 1 billion km to train and validate your Neural Network (NN) for computer vision. Now a new cam is launched on the market (32 bits per color, 10k) : If you want to use your NN, you will degrade quality of images and put them into your system. If you want to take advantage of your better camera, then you must capture 1 NEW billion km with the new cam and train a new NN.
NOT VERY INDUSTRIAL!
NEXYAD has developed a methodology to get same KPIs with a very picky compact database (easy to reshape the database with new sensors) : A.G.E.N.D.A. (Approche Générale des Etudes Neuronales pour le Développement d’Applications), published in scientific papers in the 90’s – yes – the 90’s by NEXYAD team.

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SafetyNex and the “S” Curve Theory

RELATIONSHIP BETWEEN DRIVING RISK AND ACCIDENT : THE “S” CURVE THEORY

Let’s say in a manufacture there is a very dangerous machine that may grind up your hand. If you are 10 km away from the machine, risk is “very” low. If you are 1 km away from the machine, risk is the same. If you are 10 m away from the machine … risk is still very low … but if you come closer (let’s say 10 cm), suddenly risk becomes high ! This is not linear. In road safety, the Artificial Intelligence algorithm SafetyNex estimates 20 times per second the driving risk you take, and many people ask about relationship between “risk you take” and “accident”. This relationship is not deterministic (probabilities must be used) : risk is not linked directly to accident but rather to accident frequency (or probability)… and the relationship is a non linear curve called a “S” curve as shown on the figure below. It is possible then to use it to alert human driver (Vocal Driving Assistants) or to control autonomous driving (Autonomous Vehicle) in order to keep risk under the threshold of the “S” curve or not too far after the threshold. SafetyNex was calibrated in order to have 95% of accident frequency just after the threshold (validated on 50 million km).

Click image to enlarge

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Congresses & Events

NEXYAD CEO on Mobility TV about Road Safety applied to AV

Use the YouTube translation to follow with your language.

Gérard YAHIAOUI, CEO of NEXYAD, participed in a TV show on Mobility TV about the Autonomous Vehicle, where he explained the value of SafetyNex for road safety applied to Autonomous Vehicle. The other guests were Jean-Pierre CARNEVALE, departement director for Ipsos, Abdelkrim DOUFENE from IRT SystemX, and Hervé GROS from SIA (automotive engineers society), the talk show was animated by Patrick ROGER for Auto K7.

First French Congress devoted to Autonomous Vehicles

Last 25-26 june, SIA and URF jointly organized the first French conference on the autonomous vehicle in order to cross the views of the whole scientific and technical communities : car manufacturers, suppliers, road infrastructures, telecommunications and transport operators in connection with the national and territorial public decision-makers.
200 experts, 4 sectors, a dozen of exhibitors, 38 interventions, keynotes by Anne-Marie Idrac (AV special adviser), Cédric Villani (AI special adviser) and Luc Chatel (President of PFA), 1 round table of industrial leaders and the public sector, or how to draw up the state of the art for the biggest technological change in mobility and transport.

The goal is to accelerate the capacity for innovation everyone to serve everyone, by bringing all stakeholders together under the aegis of the most relevant experts for the autonomous vehicles of tomorrow.

Gerard Yahiaoui, CEO of Nexyad was invited to talk about SafetyNex on a focus about Intelligent Onboard Technologies.

Gérard Yahiaoui explaining SafetyNex

A.I. key of profitability Conference at TNP

This thursday 14th june, TNP, a consulting firm specializing in business transformation, inaugurated its new generation start-up accelerator! The audience follow interesting conference about Artificial Intelligence in Mobility field.

Transports Publics, the European Mobility Exhibition, is the not-to-bemissed biennial exhibition for all the key players in public transport and sustainable mobility from across Europe. Over 11,000 highly qualified participants come together over three days in Paris to discuss the latest innovations for urban, interurban and regional transport, as well as green mode transport.
Transports Publics is recognised as the leading European showcase for innovations in equipment, services and policies relating to the entire mobility sector, bringing together leading European decision-makers from transport and politics.

This year, we could see for the first time, the new technology for rear-vision on buses,coaches and trucks : the camera-based system instead of mirrors. We visited Vision Systems booth that is the first firm to propose such system with its Smart-Vision product.
Smart-Vision allows to save about 5% gas consumption, that reduces CO2 emissions; the cockpit screens for driver are much more efficient than mirrors, they eliminate sun glare or reflexion problems and of vehicles lights, and they increase visibility at night and tunnel conditions.
This solution has been integrated in Heuliez and Irizar buses as shown on the exhibition, and public transportation operators companies in Europe have already adopted Smart-Vision.
Vision Systems also shown a lidar perception system around vehicle called Savety-Front for collision avoidance.

The trend of 2018 was on electrification for buses in particular, and public transporation in general.
Autonomous pod or shuttle was not yet present except outside with Navya.

For the third consecutive time the Groupement ADAS (cluster) was present to the Autonomous Vehicle Technology World Expo at Messe Stuttgart 5-7 june 2018. Intempora and Nexyad represented the french-canadian cluster sponsorised by Mov’eo Imagine Mobility.
Edition 2018 was quite good, we propose a focus on some companies we saw to the convention.

The Elektrobit industry experts came to share their experience on how to effectively manage a functional and open HAD software architecture on an adaptive AUTOSAR infrastructure. They were keen to demonstrate how the functional software architecture with open interfaces and software modules is integrated on a high-performance microcontroller using an AUTOSAR adaptive middleware. In addition to the functional challenges, the transmission of integrity levels of automotive safety could be explained to you. EB booth visitors could appreciate why the advantage of combining an open software framework for automated driving with a reliable operating environment reduces time-to-market due to fast integration and first system-level testing.

ESI Group is a leading innovator in the field of virtual prototyping software and services. A specialist in materials physics, ESI has developed a unique skill to help industrial manufacturers replace physical prototypes with virtual prototypes, enabling them to manufacture, assemble, certify and pre-certify their future products. Coupled with the latest technologies, ESI now wants to anchor virtual prototyping in the broader product performance lifecycle concept, which addresses the operational performance of a product throughout its life cycle, from launch to disposal. The creation of a hybrid twin, based on simulation, physics and data analysis, allows manufacturers to deliver more readable and connected products.

Sigra Technologies was exhibiting its autonomous driving system, its components and services called Deep Einstein. Its products range from drive-by-wire embedded systems to decision-making based on a deep neural network. The company believes that an approach based on deep learning is the best way to handle hard-to-solve cases using traditional algorithms. During the exhibition, Sigra presented its new system for the demonstration of autonomous driving.

StreetDrone is an ambitious UK self-driving startup with a rich automotive, motorsport and entrepreneurial DNA. The streetDrone team is passionate about putting the AV revolution into the hands of the many , not just the few, providing the platform , data management system and functional safety, thereby allowing businesses and institutions to focus on their own development goals without having to worry about the cost and complication of vehicle hardware and systems engineering. StreetDrone is enabling the next generation of engineering to be involved in what is the most exciting area of technology today.

Veoneer is a leading system supplier for ADAS autonomous driving AD and advanced brake control solutions, and a market leader in automotive safety electronics products. With one of the oadest product portfolios in the larket, Veoneer is the forefront of innovation in the current revolution of the automotive industry. Veoneer takes on the challenge of automation and human-machine tion as vehicles become increasly intelligent.

Vector informatik is a leading manufacturer of software tools and embedded components for the development of electronic systems and their networking with many different systems from CAN to automotive Ethernet. Vector has been a partner of automotive manufacturers and suppliers and related industries since 1988; Its tools and services provide engineers with the decisive advantage to make a challenging and highly complex subject area as simple and manageable as possible. Worldwide customers in the automotive, commercial vehicles, aerospace, transportation and control technology industries rely on the solutions and products of the independent Vector Group for the development of future mobility.

The four algorithms products of Nexyad are now well known by automotive profesionals. Numerus companies worldwide integrated SafetyNex the on board Driving risk assessment in real time, combinable with the three camera-based modules: RoadNex for road detection (edges of road and bitumen free space); ObstaNex for obstacles detection (vehicles and pedestrians); and VisiNex for visibility measurement (fog and heavy rains detection, reliability, distance of visibility, etc.)

The new video on SafetyNex, on board driving risk assessment in real time.

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CNEJITA Seminar on Artificial Intelligence:who will be responsible ?

April 10th, CNEJITA (National Company of Legal Experts on Computer Science and Associated Techniques) organized a Seminar, whose objective is to determine the responsibility in terms of artificial intelligence through the understanding of technology and the dialogue with the actors of the sector.
It is therefore around this theme of topicality and future which is the artificial intelligence that the best experts in terms of computing met at the Commercial Court of Paris.

AI: concepts, technological breakthroughs and new risks
– Understanding the Concepts and Landscape of AI – Jean-Claude HEUDIN (Artificial-Creature.com – Teacher Researcher in AI)
– IA: state of play and perspectives – Jean-Philippe DESBIOLLES (IBM head of France IA WATSON)

Roundtable – Which Expertise fo AI ? was animated by Serge MIGAYRON (Honorary President of CNEJITA)
– The acceptability and limits of IA – JA CAUSSE (CNEJITA Expert)
– The Autonomous Vehicle and Traceability of IA – Jean-Louis LEQUEUX (Former President of VeDeCoM Tech)
– Auditability and risk control in the design of an IA – Gérard YAHIAOUI (NEXYAD)
– Evolution of the world of insurance, towards an objective responsibility – Nicolas HELENON (Co-manager Firm NEO TECH Assurances)

– Introduction to Classical and New AI Concepts by Law: Applicable Regime and Evidence – L SZUSKIN (BAKER McKENZIE Lawyer)
– Tort liability in the face of AI: adaptation of traditional categories or creation of a responsibility specific to AI? – P GLASER (Lawyer TAYLOR WESSING)
– Contractual liability in the face of the IA: risk management during the contractualization of an IA system – FP LANI (DERRIENNIC Associate Lawyer)
– Synthesis on the current legal landscape – G de MONTEYNARD (Attorney General at the Court of Cassation)

Gérard YAHIAOUI, CEO of NEXYAD

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SafetyNex : driving robot maybe will mitigate human errors,but first they have to imitate good drivers

BEWARE with the statistics : “94% of severe personal damage accidents are due to human errors” doesn’t mean that you’ll save 94% of severe accident with autonomous driving : drivers do not only make mistakes they also drive well (1 accident every 70 000 km, 3 dead every billion km – OCDE) … It is important to study also good driving and near misses (when driver has the right behaviour to avoid accident or to mitigate severity)… That’s what NEXYAD did during 15 years of research programs on road safety ^^ (that led to SafetyNex). See image (if you do not provide the “green” features, you will lose lives more than you gain with your driverless car. Our AI algorithm SafetyNex was made for this.

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“Theory of Water Flush” and Impact on the Prevention of Accidents for Autonomous Vehicles

“THEORY OF WATER FLUSH” AND IMPACT ON THE PREVENTION OF ACCIDENTSFOR AUTONOMOUS VEHICLES

by NEXYAD

INTRODUCTION
Let’s suppose that the flush does not exist in our toilets, and then let’s suppose that engineers able to create complex systems or even “systems of systems” are consulted to invent it, and that they apply exactly the same method than they do in the field of ADAS and Autonomous Vehicles.

METHOD OF SCENARIOS
We propose to apply the method of scenarios, which consists in crossing all the factors that can modify the situation, then in each case of the complete combination, propose a solution. For this, it is necessary to note the number of possible shapes for the tank, the possible volumes, all the possible locations for the water supply entry, the possible diameters of the inlet pipe, the flow rates and possible pressures of water, the possible residual water levels before filling. We can generate the combinatorial of these factors, which allows us to generate all the possible scenarios of the “flush” problem. In each case, it is possible to give a solution, namely, the duration of filling of the tank (opening and closing of the water tap).

This approach is fully compatible with deep learning, which will also interpolate between two reference cases (quality of interpolation/generalization to be controlled, of course) if characteristics had to drift over time. Of course, the tank must integrate a system of sensors to evaluate the configuration (diameter of pipe, pressure of water, position pipe, capacity of the tank, etc …). We can use a camera, lasers, ultrasounds, etc. So that this recognition of situation is as accurate as possible. For such an approach, automation/control engineers talk about open-loop (feed forward) control because the data flow is as follows:

COST AND ROBUSTNESS OF THE SCENARIOS METHOD
It is easy to understand that the flush thus designed will be perfectly functional (there is no reason for it does not work), but for a high cost due to the sensors to integrate. Similarly, the robustness of the system to a measurement error or to a bad situation recognition is not guaranteed : we can very good to fill too much or not enough. The accuracy of the configuration case recognition is very important.

SOLUTION OF WATER FLUSH IN THE REAL WORLD
If you have the curiosity to disassemble your flush, you will notice that it is much simpler than the system described above: A float indicates when the water supply valve should be closed. The figure is as follows:

Automation engineers call this a closed loop control (servo control). The feed forward “open” control is reduced to “open the tap thoroughly without worrying about the flow of water, the volume of the tank, and turn off the tap as soon as the float asks for it “. Note that this method works regardless of the configuration of the flush : we do not even need to know the volume of the tank that can be modified (for example: by filling half of the tank with glass beads) without affecting the operation of the flush. It is a robust and cheap system.

TRANSCRIPT OF THESE REMARKS IN THE FIELD OF ADAS AND AUTONOMOUS VEHICLES:SERVO CONTROL IN DECISION
The information processing chain of the autonomous vehicle follows the general feed forward form :
NEXYAD has developed the SafetyNex system which dynamically estimates in real time the risk that the driver (human or artificial) takes. However, the autonomous vehicle may be functionally specified as follows:

“transport someone from point A to point B as quickly as possible, and safely.”

The “quickly” aspect is the historical business of the automobile. The “safely” notion integrates intrinsic safety of the system (its dependability: it should not explode, sensors or power supply may not be disabled, etc.), and since it is a vehicle, its ability to move with a good road safety, that is to say by “not taking too much risk in driving”. Since SafetyNex estimates this driving risk dynamically and in real time, it can be said that SafetyNex is a dynamic indicator of “SOTIF” (Safety Of The Intended Function). SafetyNex acts as a “driving risk float” : when the risk arrives at the maximum accepted level (like the float of the flush) we stop the action that raised the risk (example: we stop accelerating or we slow down). Thus, the response of an autonomous driving system is made adaptive (at the decision level) : even if the feed forward open loop is not perfect, it can correct itself to take into account, among other things, the instruction and the measure of driving risk. This system is completely independent of the automatic driving system in terms of information processing, so it represents redundancy of processing.

SafetyNex uses to estimate risk :

. risk due to inadequacy of driving behaviour to the difficulties of the infrastructure : navigation map, GPS, accelerometers

. risk due to inadequacy of driving behaviour to the presence of other road users (cars, pedestrians, …) : data extracted from the sensors (camera, lidar, radar, etc) such as “time to collision”, “inter distance (in seconds)”, number of vulnerables around, etc.

. risk due to inadequacy of driving behaviour to weather conditions: in particular to atmospheric visibility (fog, rain, snow, sand, penumbra). Knowing that when visibility is low, vehicle must pay more attention (and slow down) even if this autonomous vehicle is not impacted by the decrease in visibility (if it only uses a lidar for example) because the avoidance of an accident is done at the same time by the two protagonists : if one of them (pedestrian, human driver), does not see the autonomous vehicle, then it finds itself only to be able to avoid the accident, which doubles the probabilities of a potential accident.

. other

The use of SafetyNex allows to make adaptive an artificial intelligence of autonomous driving, on the following diagram :

If you have a lean computer, then you only apply one loop between t and (t+1) as it is shown on the figure. If you have a powerful computer, you can then even simulate a big number of decisions and take the less risky one (like automaticians do with predictive control systems). Of course, SafetyNex is only ONE way to close the loop (on a crucial notion : driving risk). This figure may be extanded to other variables of contol that make sense for an autonomous vehicle. More complex adaptation rules may switch from a decision to another if risk simulation shows that finally it is less risky (ex : slow down or turn wheel ?).

CONCLUSION
SafetyNex uses the map in addition to sensors (same sensors as the driving system or parallel tracks) and does not need to accurately identify the situation but instead to estimate a risk (this is a different task). SafetyNex is a knowledge-based AI system (knowledge extracted from human experts in road safety, from 19 countries – Europe Japan USA – who validated the system over 50 million km. Total research program duration : 15 years). This technology is still being improved, of course, but it can already be integrated into autonomous vehicles and avoid a large number of accidents by its ability to make the system adaptive to unknown situations. In particular, in the case of autonomous urban vehicles (autonomous shuttles, robot taxis), the adaptation of driving behaviour to complexity of infrastructure is made possible by SafetyNex, which decodes this complexity by reading the navigation map in front of the vehicle. SafetyNex makes the autonomous vehicle anticipate more by following “rules of safety” : with SafetyNex emergency situations (that still will need emergency braking and other emergency actions) become much more rare. Autonomous vehicle acts like an experienced cautious driver. Note : if you modulate Maximum Accepted Risk, then you modulate aggressiveness of the autonomous vehicle. This might make sense not to let the autonomous vehicle trapped in complex human driving situations (where the autonomous vehicle would stopped indefinitly).

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4 disruptive AI algorithms for automotive mobility

. ObstaNex detects obstacles with a simple cam (a la Mobileye).
What is disruptive ?
ObstaNex runs in real time on a regular smartphone… it means it doesn’t need a big computing power to run. It can be trained/re trained on a “small database” using the methodology A.G.E.N.D.A. (Approche Générale des Etudes Neuronales pour le Développement d’Applications or General Approach of Neuronal Studies for Application Development) – important is you improve your cam !

. RoadNex detects drivable part of the lane borders and free space.
What is disruptive ?
RoadNex works even in the Streets of old cities as Paris, London or Roma, and it runs in real time on a regular smartphone. it means it doesn’t need a big computing power to run.

. VisiNex detects lacks of visibility (fog, heavy rain, snow, sand storm …).
What is disruptive ?
VisiNex is an artificial vision tool which is correlated with human perception. If there is something to see, VisiNex is able to give a score of visibility. Except Daimler, we haven’t seen such a military background-based detection elsewhere.

. SafetyNex is the only fusion Artificial Intelligence algorithm (sensor + map fusion) that estimates driving risk dynamically and in real time.
What is disruptive?
SafetyNex allows to have an explicit value of driving risk. It is a total revolution for car insurers, fleet managers, and autonomous driving engineers. These algorithms are already under integration into products for telematics /connected car, ADAS, Autonomous Vehicle.

The Connected Automotive Conference, held March 13, 2018 in Paris, is the French reference in conference on the connected vehicle.
Several themes were discussed around selected guests:
– What is the innovation “Made in France”? Decryption of the latest advances and ongoing pilot projects that will bring major changes in the field of mobility.
– New expectations of the French. Analysis of the latest studies conducted with citizens and put in perspective with the results around the world.
Which ADAS will integrate the automobile tomorrow? After smart parking and cameras, what driving assistants will be used in tomorrow’s vehicles and for what use?
– How will AI change the lives of motorists? From GAFA to start-ups, everyone dreams of designing the intelligent assistant of the motorist. The relationship with the brand will be transformed.
Then, followed interview, key-note, startup contest and experts workshops, all day long.

Gérard YAHIAOUI, CEO of Nexyad, was invited to participate at the conference as an expert in Articicial Inteligence, Advanced Driver Assistance Systems and Highly Automated Driving.

Here is a news in French press that talks about the Academic Chair that the cluster of startups and SMEs « MOVEO Groupement ADAS » organized with INSA Rouen.
NEXYAD is part of this cluster of high-tech startups and SMIs (on ADAS, connected car, and autonomous driving) and is quoted in this article of Journal du Net (French spoken), they interviewed Mr Aziz Benrshair, director of the “Autonomous and Connected Vehicle” Academic Chair launched by INSA Rouen :Comment ces partenaires contribuent-ils concrètement ?

The value of driving risk notion for Telematics, ADAS and Autonomous Driving.

by NEXYAD

Every year, more than 25.000 persons die on roads in Europe which has the safest infrastructures anyway. Brasil, Russia, USA, have more fatalities and the situation is worst in development countries. Everywhere people are aware by these risk for their health or life. Driving can be dangerous for drivers and passengers, however most of people accept these risk fairly minimal (in average three dead by billion km in OECD countries) for all advantages of fast point to point terrestrial mobility. But by the way, what is exactly what people use to call driving risk?

Let’s take an example, if someone plays Russian roulette: probability to die is one on six when one pulls the trigger. If one decides finally not to play, probability to die with a bullet in the head disappears completely. If you pull the trigger, risk to die is 100% (although probability is 1/6).
Another example: if a car is static parked into garage, then driving risk is zero. On the opposite, if a car passes a stop sign at 20km/h, driving risk taken by the driver is equal to 100%: driver takes the full risk). Probability depends on the traffic at the intersection.

More generally, driving risk taken by driver (and we talk about “the risk you take” a priori) will goes from 0 to 100% depending on the adequate of driving behaviour to driving context. This driving context has several dimensions: complexity of infrastructure, traffic of other road users, weather conditions, etc. Inadequate of driving behaviour to complexity of infrastructure can predict 75% of accident.

SafetyNex and the compliance Package ofCONNECTED VEHICLES AND PERSONAL DATA

In march 2018, french CNIL will publish the final version of the Compliance Package for the Connected Vehicles and Personal Data.

NEXYAD appears in the list of Bodies consulted by the CNIL (p.3). An interesting article about the collected data shows that SafetyNex is fully compliant with french law and recommendations for European Union (p.25).

Extract :

DATA COLLECTED

The data control shall only collect personal data that are strictly necessary for the processing. In the case of a contract for the provision of services, the only data that can be collected are those that are essential for the provision of service.

Concerning data relating to criminal offences:

For purpose 1 (model optimisation and product improvement) and 3 (commercial use of the vehicle’s data): except in the case of specific legal provision, data that are likely to reveal criminal offences shall not be processed by legal persons who do not administer a public service,
except to defend their rights in court. However, that data can be processed locally, directly in the vehicle, in accordance with scenario No. 1, in order to give the user control over that particularly sensitive data and limit as much as possible the consequences on privacy.

For the second time, NEXYAD went to CES (2018) in Las Vegas (from 9th to 12th of Jan).

Takeoff at Paris CDG AirportArrival in Las Vegas

Flight to Vegas from Paris is long but it’s worth the trip for a high-tech startup like NEXYAD.

Of course, for NEXYAD, it is the year of deployment in series for our onboard software modules (Connected car/Car telematics, ADAS, Autopilots, Drive and Car sharing), and especially for SafetyNex (estimation of driving risk 20 times per second), and we had organized for a while 6 meetings per day : ADAS and Telematics OEMs that are already currently integrating SafetyNex, and of course new prospects. Very good new contacts too with qualifies prospects from the USA, Japan, Europe.
We also got some interest for RoadNex that integrates a computer vision based free space detection that works perfectly for large round abouts and intersections. We brought a real time RoadNex implementation into an android smartphone (using the smartphone cam and CPU) and we could do some real time demos that show that RoadNex works in a regular smartphone in real time (for those who care of CPU consumption) :

This year we had a barrow on the LeddarTech booth located at Central Plaza, close to Faurecia, Valeo, Google, Visteon, etc … : LeddarTech is member of the MOV’EO Groupement ADAS, and the whole Groupement was part of the « LeddarTech ecosystem » showcase area.

Leddar Ecosystem Pavillon at LVCCGroupement ADAS Desk

We also used some time slots to do our homeworks on Business Intelligence and visited many boothes including competitors of NEXYAD.
From this visits we could extract some heavy trends : of course, CES deals with quite EVERY subject, then we focused on mobility and what is connected to mobility issues.
First, we must notice that 2018 is THE year of Lidar :
Of course, our partner LeddarTech, but also many other solutions from Startups to Major automotive companies :

LeddarTech;

InnovizVelodyne

QuanergyPioneer

Startup II – VIStartup AEye

Toyota

Another heavy trend is smart cities :

Itron (Energy issues) Deloitte (Complete systems and strategy)

LoRa (IOT) Ericsson (Telecom 5G)

Mobility was a big part of Smart Cities and Urban mobility this year in Las Vegas.
Some soft mobility solutions (electric and connected 2-wheels vehicles) :

As you may notice, you can find shuttles from : a pure leader player, an IT major firm, a major car manufacturer, a major operator of urban mobility, and a high-tech startup.

At least, another completely new trend is the autonomous flying vehicles :

Volocopter

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SafetyNex animated video of a use case :The Car Insurer’s Choice

SafetyNex by NEXYAD is a Driving Risk Assessment App/API for prevention (accompanied driving, young drivers, individuals, professional drivers, seniors) in every kind of 4 wheels vehicle. SafetyNex is worth for UBI (risk profiles, usage profiles) at the end of every trip; reduction of costs (lower rate of accident and in particular of personal injuries + transformation of some severe personal injuries accidents into material accidents); Detection of behaviour modifications in time and Distraction detection (mobile phone …) : under implementation.

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Nexyad in media

Rémi Bastien interview, the new President of competitive cluster Mov’eo and also President of VEDECOM Institute and VP Automotive Prospective of Renault Group.

For English subtitles click the button on the video

Mov’eo is a Mobility and Automotive R&D competitiveness cluster, which since 2006 has been mobilizing its energies at the service of its members to meet the objectives assigned by the State to competitiveness clusters: to foster the development of collaborative projects between members, to contribute to development in the regions of companies, in particular SMES, and to promote innovation in the sector.

Created in february 2014, VEDECOM is a French Institute for Public-Private Partnership Research and Training dedicated to individual, carbon-free and sustainable mobility.

The new MOV’EO President quote NEXYAD SafetyNex at the beginning of its intervention…

Last year Nexyad won the special prize “Coup de Cœur” by french insurers of Cercle Lab with SafetyNex the driving risk assessment App in real time. For this, Gerard Yahiaoui CEO of Nexyad handed the 2017 new prize to the winner KAP-Code represented by Adel Mebarki. Kap-Code is dedicated to improve the care of chronic diseases and the detection of drug safety signals on social networks thruth 3 solutions : helping patients and health advisors with connected objects, Digital Health that allows profesionals to provide care for their patients and harnessing Big Data for science.

SafetyNex driving risk assessment(20 times per second while driving): anticipation of danger

SafetyNex estimates driving risk 20 times per second, during driving (real time).
On the following figure, you can see risk rising when approaching a stop sign with an inappropriate car speed :

Speed of the car is quite high before the STOP sign and Risk goes to the maximum with a vocal alarm to the driver which have time to slow down or brake to stop.

This estimation is computed INSIDE the local device (inside the car). Current implementation is on smartphones (IOS and Android), then computing of risk is completely done INSIDE the smartphone : that makes SafetyNex compliant with all driver’s privacy regulations and laws in Europe.

Nicolas du LAC, INTEMPORA, and Gerard YAHIAOUI, NEXYAD, presented their innovations and explained how the MOVEO Groupement ADAS helps to be stronger for their innovative startups.
Nicolas talked about RT-MAPS that is a software tool for R&D, making easy the task of developing applications with multiple sensors (cameras, lidar, radar, …) that of course are not synchronized and that must collaborate through algorithms of sensor fusion in order to get good objects detection and recognition.
Gerard talked about SafetyNex that is an onboard real time module that is the only module in the world that can estimate driving risk 20 times per second. Self-driving car can then know the risk it takes with and it simplifies the development of autopilot (example : “if risk too high then slow down”).

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Bitumen Free Space Detectionby Nexyad RoadNex on Smartphone

RoadNex detects free space on road with negative detection of obstacles as vehicle on the video below.

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Nexyad present with Groupement ADAS at Equip’Auto 2017

Philippe Orvain, CEO of Nomadic Solutions

Nexyad was present with Groupement ADAS at Equip’Auto Congress in Paris. Groupement ADAS is a SME’s cluster : 10 companies with expertise in the field of Advanced Driver Assistance Systems, Connected car and Autonomous vehicle. Philippe Orvain CEO of Nomadic Solutions and competitiveness cluster MOV’EO Vice President has responsed to journalist Laurent Meillaud on Congress TV channel.

The NEXYAD company is currently developing the construction of a database for the validation of systems of driver assistance and driving delegation, (ADAS and Autonomous car) using the AGENDA methodology published in the 1990s by Gérard Yahiaoui in the field of machine learning and artificial neural networks applications. Here is an example of ground reality : ground reality is needed in order to automate performance / KPIs measurement when you modify the perception system.(methodology initially intended to handle, among other things, the construction of learning databases and tests for the implementation of neural networks).

As many people know now, NEXYAD has been developing the first real time driving risk assessment system called SafetyNex.

SafetyNex is currently available in B2B :
. as a smartphone App (Android and IOS)
. as a real time driving risk assessment API that OEMs and Insurers may integrate into their own smartphone App or into their own telematics or ADAS device (Android, iOS, Linux, Windows).

This real time driving risk assessment module has been validated on 50 million km, and applies proven methods for risk assessment, using, for instance, the Frank E. BIRD “safety triangle” concept, and running in real time a knowledge-based system AI that has been built by NEXYAD since 2001. It took 15 years to extract thousands of road safety knowledge atoms from experts of 19 countries. Some of this knowledge is directly operational, some is deep knowledge on detection theory (a mix of Information Theory and Knowledge on Human Brain abilities). And of course, SafetyNex also applies fundamental knowledge on mechanics (braking abilities, …) including complex issues such as grip for example.

Complex Automation MUST be ASIL ISO 26262.
Artificial Intelligence CANNOT BE ASIL ISO 26262 (by definition) and acts only on parameters of Complex Automation doing ++/– – variations, never skipping « reflexes actions » (emergency braking, etc), but allowing anticipation speed adaptation to reduce frequency of emergency situations (and then give more margin to reflexes actions and also improve comfort). Maximum acceptable Driving Risk can be changed depending on driving situation in order to set « aggressivity level» of HAV.

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Welcome to YOGOKO, new member of “MOV’EO” Groupement ADAS cluster

In november, cluster Groupement ADAS, from Mobility and Automotive R&D competitiveness national cluster Mov’eo, welcomed YOGOKO as new member. It makes eleven players like a football team, and we hope to score goals in the Automotive market competition.

YoGoKo is a startup company founded in 2014 by employees from three research institutes : Mines ParisTech, Telecom Bretagne and Inria. YoGoKo makes use of software developed in teams specialized in Internet technologies (RSM at Telecom Bretagne) and robotics (CAOR at Mines ParisTech and RITS at Inria). These research teams have been working together since 2006 on innovative communication solutions applied to Intelligent Transportation Systems. They contributed to several collaborative R&D projects related to ITS (CVIS, ITSSv6, GeoNet, DriveC2X, SCORE@F, …).

In 2012, these laboratories engaged together into the development of a common demonstration platform which comprises connected vehicles (fleet of conventional vehicles from Mines ParisTech and fleet of autonomous vehicles from Inria), roadside equipments and cloud-based services.

YoGoKo demonstration platform was finally revealed on Feb. 11 th 2014 during the Mobilité 2.0 event organized by the French Ministry of Transport. This successful demonstation and the extremely warmfull feedack gained at this occasion triggered the launch of YoGoKo as a company.

A lot of professionals that must cope with road safety observe accident through statistics : it seems to be normal to think that safety is low where there are a lot of accidents and that safety is high where there are few accidents.
This reality tends to make people confuse the two notions : risk and accident.
And since you stay at the statistic level, then it works : if 99% of people that played russian roulette more than 50 times have died (accident), then you can say that russian roulette is risky (risk).
Insurance companies, fleet managers, have taken into account those statistics, in order to estimate their future costs, and compute their pricing.
But now, digital connected devices are available at the very individual and local level : telematics (professional devices installed into cars), smartphones, connected car, can estimate the driving behaviour in real time and they know exactly where you drive.
Then, what this new technology brings to risk assessment ? and can you still apply at the individual level the ideas that was set at a population (statistics) level ?
That question was studied in 1969 by an American University Professor that was also a researcher for the company “Insurance of North America”, Frank E. BIRD, and a key notion was then used : the “incident” or “near miss accident” or “quasi accident”. It was shown that the risk you take does not lead to accident but to “quasi-accident”. Indeed, even in very risky situations, accident can be avoided most of the time at the very last second ! Frank E. BIRD worked on what was called “The Triangle of Risk” or “Safety Triangle”
Sometimes, you do not have luck … and then you have an accident instead of having a quasi-accident.

Example of Statitical Relationship in Risk Assessment : from Behaviour to Fatalities

Then accident is the confluence of “risk you take” and “bad luck”. It is interesting to notice that, if you do not study the individual and local (in space and time) level, so if you consider a large population of drivers during a long duration, then “bad luck” automatically disappears… and so risk can be measured by observation of accident. But at the individual and local levels, risk cannot be measure by observing accident.
It is interesting to read about Safety Triangle and then have a clear idea of links between RISK, ACCIDENT, SEVERE PERSONAL INJURIES.
In road Safety concerns, researchers and experts have been working during 50 years on this concept of quasi-accident and they accumulated data and knowledge about this key notion. Let us resume the russian roulette comparison : pulling the trigger is the quasi-accident … and sometimes you die (accident). But even before playing such a “game” you KNOW that it is risky.
The knowledge of risk is represented by a collection of cause-effect relationships.
There is a knowledge-based artificial intelligence system that gathered the knowledge from road safety experts and researchers (that work mainly on road infrastructure) and that is now available in order to assess driving risk in real time : SafetyNex developed by the company NEXYAD. SafetyNex is the “thermometer” of driving risk and it alerts the driver BEFORE the dangerous situation, letting time to slow down and then potentially to avoid accident, to reduce severity (less personal severe injuries), …
Obviously, markets are :
. car insurance (prevention, severity, UBI)
. fleet management (prevention, reduction of costs, fit in regulations and laws)
But even the automotive can take benefit of suche a real time driving risk assessment module :
. intelligent navigation with risk vocal alerts
. automatic triggering of braking for ADAS (if risk too high then slow down)
. driverless cars : giving to the artificial intelligence that drives the car the perception of the risk it takes…
SafetyNex opens the door to a new generation of onboard applications for every field of automotive sector that is concerned with risk and safety.Read more

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Nexyad at AutoSens Brussels 2017

AutoSens took place at the AutoWorld Museum in Brussels September 19-21.
To answer the issues of Connected Cars and Autonomous Cars, engineers need first to give eyes, ears and A.I. to future vehicles. Sensors will play this crucial and difficult role of replacing the human senses.
Engineers and sensors providers met for three days of conferences and workshops.
Groupement ADAS was present with Leddartech the lidars canadian company that rose 100 M$ funding, New Imaging Technologies with their unique high dynamic range camera sensors, Intempora that provide famous RT-Maps, and of course Nexyad presented his three camera-based software modules for Road Detection – RoadNex, for Obstacles Detection – ObstaNex, for Visibility Measurement – VisiNex and SafetyNex – the Road Safety system with sensors fusion and data fusion (digital map, accelerometers, GPS, cameras, lidars, radars, ultrasounds, weather data, traffic data, etc.).
New players appeared as Crowdflower or Mighty Ai, they are plateforms that help you process your data or images very quickly by dividing the workload with very many people registered online.

3 days of exchanges and conviviality at the service of Innovation + Business Meetings driven by THE NEW NEEDS OF CONNECTIVITY.Read more about the Event

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Connected & Self-driving Car Meetup #9

Nexyad was invited to the Connected & Self-driving Car Meetup #9 at Le Square (Renault’s innovation lab in Paris), on september 13.
Thanks to the perfect organisation of Laurent Dunys and Bruno Moncorge.
A large audience listened presentation about vehicles and data security with Nabil Bouzerna of IRT SystemX. Finally, Jean-François Menier, lawyer at Elyos Avocats gave a very interesting wrap-up about the potential responsibility of a driver in the case of a connected / self-driving car accident and of course about driver and passengers safety with SafetyNex App : real time driving risk assessment.

MOV’EO Groupement ADAS built an academic chair with INSA ROUEN (option Intelligent Transportation) on ADAS and driverless cars.
The first course was given by Gérard YAHIAOUI, CEO of NEXYAD, the 13th of September 2017 in Rouen : presentation of key notions (near missed accident, driving risk), and presentation of SafetyNex (real time driving risk assessment) and applications to car insurance, fleet management, ADAS, and driverless cars.

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Sensor fusion and data fusion with SafetyNex

SafetyNex is a real time driving risk assessment system. Of course, Driving Risk makes everyone think of car insurance and fleet management. And it is a natural application (deployment has already started). But it is important to note that Driving Risk is also a key notion for ADAS and Driverless car.

Indeed, Driving Risk happens when there is no adequation between Driving Behaviour and Driving Context. ADAS and Driverless act on Driving Behaviour :
. ADAS modifies Driving Behaviour : braking when the human driver did not, etc …
. Driverless car creates Driving Behaviour : there is still a driver called “artificial intelligence”.

So you can now imagine that if you have the opportunity to ESTIMATE adequation between Driving Behaviour and Driving Context, then you can build much more relevant ADAS and Driverless Artificial Intelligence (adequation or inadequation).

You may notice that Driving Context is measured through heterogenous sensors and data streams. It brings no difficulty to SafetyNex that uses Fuzzy Sets and Possibility Theory to estimate adequation, givin a Driving output called Driving Risk (that you should want to minimize under constraints of mobility efficiency).

Then SafetyNex is actually a sensor and data fusion system (high level fusion), much more efficient than every fusion systems that you ever developed, because it generates a variable (Driving Risk) that is a KEY NOTION for driving and is EASY TO UNDERSTAND AND USE.

NEXYAD implemented a low cost version with only the first 3 inputs (more than 5,000 road safety rules to cope with the infrastructure dangers …) and is now implementing simple rules to take into account mobile context. Example: “the shorter the time to collision, the higher the risk”. And that’s it ! The knowledge based artificial intelligence of SafetyNex automatically does the fusion with the 5,000 rules. There is no need to “weight” the rules, as possibility theroy allows a fusion with every rule competing with the others … Elegant applied maths to a problem that most engineers describe in a so complicated way that it becomes impossible to solve.

We really encourage ADAS and Driverless engineers to come to us and simply integrates SafetyNex (low CPU consumption, easy real time, etc.) and then get NOW a proven sensor fusion and data fusion system that works. This gives ONE dimension of Driving Systemic Analysis items: Driving Risk, in real time.

Of course, if you do the systemic analysis you will find other dimensions of interest (we let you do that, we’ve done it for ourselves, trace of the military research past of NEXYAD founders).

SafetyNex is now under implementation by big ADAS OEM companies. Series deployment will start in 2018. We will be glad to help you being a part of it.

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SafetyNex : Understanding the Concept of Risk

SafetyNex App is a real time driving risk assessment. We present below 3 videos to explain as simply as possible the concept of driving risk.

Luck doesn’t change the risk that the driver takes. It means that risk taken by the « lucky risky driver » is exactly the same than risk taken by the « unlucky risky driver ». It is possible then to detect risky drivers before they have accident (anticipation of costs). Once detected, it is possible to train them (prevention program).

Because SafetyNex driving risk assessment is done in real time, it is possible to alert the driver (when risk is higher than an acceptable value), and if driver slows down, then risk never rises at the red level. It is an onboard prevention system (ADAS).

Observation of accidents on a short period of time (3 months for instance) may not show any difference between « cautious driver » and « lucky risky driver » (both of them may not have accident). It is a big problem for UBI, and SafetyNex brings the solution as it anticipates accident (sooner or later the « lucky risky driver » will have a severe accident).

Imagine a robotized car that would slow down automatically when approaching a tiny curve, or an intersection or a priority, of a stop sign, etc … if needed (i.e. if and only if the current speed and acceleration of the car is not appropriate to the driving context). Sounds interesting ?
It would be then “smooth anticipation braking” (from 0.1 to 0.3 g) instead of “emergency braking” (so easier to do and not that disturbing for driver and passengers comfort in the car). Doing this, the car dramatically decreases the probability to be kept in a dangerous situation and it let much more margin to emergency brake if still needed.
Finally, it would mean that the car follows road traffic code plus safety rules (anticipation).
This is easy to achieve using NEXYAD real time driving risk assessment module SafetyNex : SafetyNex reads “Electronic Horizon” (reading POIs and decoding shape and dimensions of the infrastructure ahead), “GPS“, “accelerometers“, and can accept additional inputs such as “time to collision“, “size of free space“, “position in the lane“, “atmospheric visibility“, alert data streams (weather, accident, traffic, …). All those heterogenous data are used (data fusion) to estimate driving risk in real time : Driving Risk (t)
Then everytime that Driving Risk(t) comes higher than an acceptable threshold value, the robotized car slightly slows down … and that’s it !SafetyNex is the result of 15 years of collaborative research and it works.
Markets : Car insurance and fleet managers (for real time alert and risk profiles recording), ADAS (for automatic predictive/anticipation brake), and Driverless car (Automated car that follows Road Traffic Code).
SafetyNex is Under deployment, please feel free to try it and put it into your own products (available as an API).
Keywords : Adaptive Cruise Control, ACC, Intelligent ACC, Intelligent Cruise Control, navigation-based, navigation-based ADAS, NB ADAS, ADAS, Advances Driver Assistance Systems, Anticipation brake, Predictive Brake, SafetyNex, Risk, Driving Risk, Real time driving risk assessment, road traffic code, SafetyNex, electronic horizon, GPS, accelerometers, time to collision, free space, size of free space, position in the lane, lane departure, visibility, atmospheric visibility, data stream, weather, accident, traffic, data fusion,…